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May 27, 2024;22 (1): 9.

Estimation and probabilistic projection of age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030.

Marcos R Gonzaga, Bernardo L Queiroz, Fl��vio H M A Freire, Jos�� H C Monteiro-da-Silva, Everton E C Lima, Walter P Silva-J��nior, Victor H D Di��genes, Renzo Flores-Ortiz, Lilia C C da Costa, Elzo P Pinto-Junior, Maria Yury Ichihara, Camila S S Teixeira, Fl��via J O Alves, Aline S Rocha, Andr��a J F Ferreira, Maur��cio L Barreto, Srinivasa Vittal Katikireddi, Ruth Dundas, Alastair H Leyland
Author Information
  1. Marcos R Gonzaga: Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil. marcos.gonzaga@ufrn.br.
  2. Bernardo L Queiroz: Graduate Program in Demography, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil.
  3. Fl��vio H M A Freire: Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
  4. Jos�� H C Monteiro-da-Silva: Graduate Group in Demography, University of Pennsylvania, Philadelphia, PA, USA.
  5. Everton E C Lima: Graduate Program in Demography, Universidade Estadual de Campinas (UNICAMP), Campinas, S��o Paulo, Brazil.
  6. Walter P Silva-J��nior: Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
  7. Victor H D Di��genes: Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
  8. Renzo Flores-Ortiz: Centro de Integra����o de Dados e Conhecimentos para a Sa��de (Center of Data and Knowledge Integration for Health) - CIDACS/ Gon��alo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil.
  9. Lilia C C da Costa: Universidade Federal da Bahia (UFBA), Salvador, Bahia, Brazil.
  10. Elzo P Pinto-Junior: Centro de Integra����o de Dados e Conhecimentos para a Sa��de (Center of Data and Knowledge Integration for Health) - CIDACS/ Gon��alo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil.
  11. Maria Yury Ichihara: Centro de Integra����o de Dados e Conhecimentos para a Sa��de (Center of Data and Knowledge Integration for Health) - CIDACS/ Gon��alo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil.
  12. Camila S S Teixeira: Centro de Integra����o de Dados e Conhecimentos para a Sa��de (Center of Data and Knowledge Integration for Health) - CIDACS/ Gon��alo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil.
  13. Fl��via J O Alves: Centro de Integra����o de Dados e Conhecimentos para a Sa��de (Center of Data and Knowledge Integration for Health) - CIDACS/ Gon��alo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil.
  14. Aline S Rocha: Centro de Integra����o de Dados e Conhecimentos para a Sa��de (Center of Data and Knowledge Integration for Health) - CIDACS/ Gon��alo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil.
  15. Andr��a J F Ferreira: Centro de Integra����o de Dados e Conhecimentos para a Sa��de (Center of Data and Knowledge Integration for Health) - CIDACS/ Gon��alo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil.
  16. Maur��cio L Barreto: Centro de Integra����o de Dados e Conhecimentos para a Sa��de (Center of Data and Knowledge Integration for Health) - CIDACS/ Gon��alo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil.
  17. Srinivasa Vittal Katikireddi: MRC/CSO Social and Public Health Sciences, Unit University of Glasgow, Glasgow, Scotland.
  18. Ruth Dundas: MRC/CSO Social and Public Health Sciences, Unit University of Glasgow, Glasgow, Scotland.
  19. Alastair H Leyland: MRC/CSO Social and Public Health Sciences, Unit University of Glasgow, Glasgow, Scotland.
PMID: 38802870 DOI: 10.1186/s12963-024-00329-x

Abstract

BACKGROUND: Mortality rate estimation in small areas can be difficult due the low number of events/exposure (i.e. stochastic error). If the death records are not completed, it adds a systematic uncertainty on the mortality estimates. Previous studies in Brazil have combined demographic and statistical methods to partially overcome these issues. We estimated age- and sex-specific mortality rates for all 5,565 Brazilian municipalities in 2010 and forecasted probabilistic mortality rates and life expectancy between 2010 and 2030.
METHODS: We used a combination of the Tool for Projecting Age-Specific Rates Using Linear Splines (TOPALS), Bayesian Model, Spatial Smoothing Model and an ad-hoc procedure to estimate age- and sex-specific mortality rates for all Brazilian municipalities for 2010. Then we adapted the Lee-Carter model to forecast mortality rates by age and sex in all municipalities between 2010 and 2030.
RESULTS: The adjusted sex- and age-specific mortality rates for all Brazilian municipalities in 2010 reveal a distinct regional pattern, showcasing a decrease in life expectancy in less socioeconomically developed municipalities when compared to estimates without adjustments. The forecasted mortality rates indicate varying regional improvements, leading to a convergence in life expectancy at birth among small areas in Brazil. Consequently, a reduction in the variability of age at death across Brazil's municipalities was observed, with a persistent sex differential.
CONCLUSION: Mortality rates at a small-area level were successfully estimated and forecasted, with associated uncertainty estimates also generated for future life tables. Our approach could be applied across countries with data quality issues to improve public policy planning.

Keywords

Lee-Carter, population forecast Life expectancy Mortality Small area analysis

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Grants

  1. MC_UU_00022/2/Medical Research Council
  2. 312609/2018-3/Conselho Nacional de Desenvolvimento Cient��fico e Tecnol��gico
  3. 303341/2018-1/CNPq
  4. 307467/2018-0/Conselho Nacional de Desenvolvimento Cient��fico e Tecnol��gico

MeSH Term

Humans
Brazil
Life Expectancy
Male
Female
Mortality
Infant
Child, Preschool
Bayes Theorem
Aged
Middle Aged
Adolescent
Adult
Child
Young Adult
Infant, Newborn
Aged, 80 and over
Cities
Sex Factors
Age Distribution
Age Factors
Sex Distribution
Forecasting
Journal Article

Word Cloud

Created with Highcharts 10.0.0mortalityratesmunicipalities2010BrazilianlifeexpectancyMortalityestimatesage-sex-specificforecasted2030acrosssmallareasdeathuncertaintyBrazilissuesestimatedprobabilisticModelLee-CarterforecastagesexregionalBACKGROUND:rateestimationcandifficultduelownumberevents/exposureiestochasticerrorrecordscompletedaddssystematicPreviousstudiescombineddemographicstatisticalmethodspartiallyovercome5565METHODS:usedcombinationToolProjectingAge-SpecificRatesUsingLinearSplinesTOPALSBayesianSpatialSmoothingad-hocprocedureestimateadaptedmodelRESULTS:adjustedsex-age-specificrevealdistinctpatternshowcasingdecreaselesssocioeconomicallydevelopedcomparedwithoutadjustmentsindicatevaryingimprovementsleadingconvergencebirthamongConsequentlyreductionvariabilityBrazil'sobservedpersistentdifferentialCONCLUSION:small-arealevelsuccessfullyassociatedalsogeneratedfuturetablesapproachappliedcountriesdataqualityimprovepublicpolicyplanningEstimationprojectionpopulationLifeSmallareaanalysis

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